The invention concerns the field of processing of comparable digital images, for the purpose of detecting (or determining) dimensional variations. They may be xe2x80x9ctwo-dimensionalxe2x80x9d (2D) images, in which case the variation will be termed surface variation, or xe2x80x9cthree-dimensionalxe2x80x9d (3D) images, and in this case the variation will be termed volume variation.
The invention applies more particularly, but not exclusively, to images termed medical images, and especially to the analysis of comparable digital images of regions of the brain, in order to study areas of interest comprising, for example, lesions or tumours, or active anatomical structures such as the heart or the ventricles of the brain. By comparable images, there is meant images taken either of substantially identical regions of the same xe2x80x9csubjectxe2x80x9d at different moments, or of substantially identical regions of two separate xe2x80x9csubjectsxe2x80x9d, or even of a single image and the associated image symmetrized with respect to a plane (or also termed xe2x80x9cchiralxe2x80x9d), when the region analyzed has a certain degree of symmetry.
In many fields it is very important to make comparative analyses of regions in order to see their evolution over time. This is especially the case in the field of high precision welding. But it is even more the case in the medical field, where the detection of lesions and/or following the course of their evolution is absolutely essential in order to adapt a treatment to a patient or to carry out clinical tests, for example. By evolution, there is meant any modification of a region, whether it is of the deformation type (mass effect) and/or of the transformation type (structural modification without deformation).
In the medical field, a set of image data forming an n-dimensional (nD) image is obtained by means of such apparatus as X-ray scanners or nuclear magnetic resonance apparatuses (MRI), or more generally any type of apparatus capable of acquiring images with variations in intensity. Each elementary part of a region represented by an nD image is defined by nspatial co-ordinates and an intensity (measured magnitude).
Thus, in the case of an MRI, the 3D image of a region observed consists of a multiplicity of stacked 2D sections, in which the variations in intensity represent the proton density of the tissues.
Techniques are already known which make it possible to detect and/or estimate variations in volume in active regions:xe2x80x94S. A. Roll, A. C. F. Colchester, L. D. Griffin, P. E. Summers, F. Bello, B. Sharrack, and D. Leibfritz, xe2x80x9cVolume estimation of synthetic multiple sclerosis lesions: An evaluation of methodsxe2x80x9d, in the 3rd Annual Meeting of the Society of Magnetic Resonance, p. 120, Nice, France, August 1994; and
C. Roszmanith, H. Handels, S. J. Pxc3x6ppl, E. Rinast, and H. D. Weiss, xe2x80x9cCharacterization and classification of brain tumours in three-dimensional MR image sequencesxe2x80x9d, in Visualization in Biomedical Computing, VBCxe2x80x296, Hamburg, Germany, September 1996.
These techniques, termed xe2x80x9csegmentationxe2x80x9d techniques, consist in delineating (or attributing a contour to) an area of interest on two images of an active region, which are spaced in time, then subtracting the xe2x80x9cvolumesxe2x80x9d contained within the two contours in order to estimate the variation in volume of the area of interest within the time interval separating the two images.
These techniques are particularly difficult to put into practice in the case of 3D images, owing to the difficulty encountered when delineating the area of interest. Moreover, the volume measurement is carried out by counting reference volume elements (voxels), of very small size, contained in a closed contour of an area of interest, the dimension of which is generally very large compared with that of a voxel. This counting can only be carried out by (semi-)automatic methods such as, for example, that termed xe2x80x9c3D snakesxe2x80x9d, which are difficult to put into practice for the non-specialist such as is generally the practitioner who carries out the analysis of the images.
The result is that the uncertainty of the measurement of the volume of an area of interest is very often greater than the estimated variation in volume, which reduces the interest of such volume measurements to a considerable extent. The accuracy of these measurements is even poorer when man has to intervene, since the measurement is then dependent on the observer.
Moreover, the areas of interest are frequently difficult to detect, owing to the fact that the materials of which they consist are not always well contrasted in the images.
The aim of the present invention is therefore to improve the situation in this field of processing of digital images of active regions.
To this end, it proposes an electronic image processing device which comprises:
registration means making it possible to determine a registration transformation between one of the images and the other, starting from the two sets of image data,
sampling means operating according to this registration in order to re-sample a first of the two sets of image data into a third set of image data relating to the same image, and able to be superposed directly, sample by sample, on the second set of image data, and
processing means which operate starting from the second and third sets of image data in order to obtain therefrom at least one set of difference data, representing differences between superposable areas of interest of the images constituted respectively by the said second and third sets of image data.
Here, the expression xe2x80x9cdifferencexe2x80x9d should be taken in the wider sense, that is to say that it may be a question of the appearance of a new area of interest, or of a modification/transformation of a known area of interest. More generally, any type of difference between the two images is concerned here.
According to another feature of the invention, the processing means comprise a calculation module to determine firstly a deformation vector field, from the second and third sets of image data, in such a manner as to make it possible to provide the set of difference data.
Preferably, the processing means comprise first calculation means for applying to the deformation vector field at least a first operator so as to provide the set of difference data, which is then termed a first set of difference data.
The processing means may also comprise second calculation means for applying to the deformation vector field a second operator, different from the first operator, so as to provide another set of difference data, which is then termed a second set of difference data.
In this way, two sets of difference data are obtained which include complementary information on the areas of interest.
The processing means may additionally comprise third calculation means for applying to the deformation vector field a third operator, a composition of the first and second operators, so as to provide another set of difference data, which is then termed a third set of difference data. This makes it possible to obtain other information on the areas of interest, complementary to those obtained with a single operator, and moreover much less subject to noise interference, and consequently more precise, owing to the fact that the respective contributions of the xe2x80x9cnoisexe2x80x9d generated by the application of these operators are decorrelated.
Consequently, the contrast of the areas of interest is significantly improved, which makes it possible to detect them more easily.
The first and second operators are advantageously selected from a group comprising an operator of the modulus type and an operator based on partial derivatives, of the divergence or Jacobian type, for example.
The modulus type operator will provide information more particularly representing movements, while the operator based on partial derivatives will provide information representing more particularly growth or diminution (volume variation or mass effect).
According to yet another feature of the invention, the processing means may comprise detection means in order to transform each first, second and third set of difference data into a fourth set of image data forming a card.
Depending on the variants, the detection means will be arranged either to allow manual selection by a user, from one of the cards, of the areas of interest, or to carry out automatic selection of the areas of interest in one of the cards.
In the case of automatic selection, it is of advantage that this selection is effected by analysis of the connex elements type.
Advantageously, the detection means are capable of determining the closed contours which respectively delimit selected parts of the areas of interest. This determination may be effected by approximation by spheres or by ellipsoids.
According to yet another feature of the invention, the processing means may comprise, separately, or in parallel with the detection means, quantification means for determining, from the deformation vector field and the second and third sets of image data, volume data representing differences of the volume variation type, so as to form the set of difference data, which is then termed a set of volume data.
This determination of the volume variations in an area of interest preferably comprises:
the association with a closed contour, representing the area of interest, of a reference contour encompassing this closed contour; the reference contour may be substantially identical to the shape of the area of interest, or may be spherical, or even ellipsoidal,
the breaking down into elements, by means of a points distribution, of the space contained in the reference contour; this breaking down of the space may be effected by means of a regular points distribution, forming a lattice, or stochastically by means of a random points distribution,
the counting of the elements contained within the closed contour of the area of interest,
the application to this points distribution of the deformation vector field, without deforming the closed contour of the area of interest,
the counting of the remaining elements within the closed contour of the area of interest, and
the subtraction of the two numbers of elements so as to determine the image data of the set of volume data representing volume variations of the area of interest.
Preferably, the quantification means calculate, in each area of interest, a multiplicity of volume variations of the selected area of interest, for reference contours which are closed and nested in one another, and comprised between the contour comparable with a point of zero dimension and the reference contour, then determine from this multiplicity of volume variations that which is the most probable. This makes it possible to improve further the accuracy of the volume variation calculation.
When the processing means comprise both quantification means and detection means, it is particularly advantageous that the quantification means operate on closed contours determined by the detection means in the areas of interest selected by the latter. This makes it possible to reduce the processing time very significantly, without thereby reducing the quality and accuracy of the results obtained, since it is not necessary to carry out quantification everywhere in the image.
Moreover, when the device does not comprise detection means, segmentation means can be provided which are intended to supply the quantification module with the areas of interest, from the second set of image data.
The invention applies more particularly to medical digital images, and most particularly to three-dimensional medical images of regions of a living being (animal or human), which regions comprise areas of interest including lesions or tumours, active or not, or active anatomical structures such as the heart or the ventricles of the brain. The second image may be deduced from the first image by a symmetry with respect to a plane.
The invention also proposes a method for processing comparable digital images, which comprises the following steps
determining a registration transformation between one of the images and the other, starting from the two sets of image data,
re-sampling a first of the two sets of image data, representing the registration image, into a third set of image data relating to the same image and able to be superposed directly, sample by sample, on the second set of image data,
determining, from the second and third sets of image data, at least one set of difference data representing differences between superposable areas of the images constituted, respectively, by the said second and third sets of image data.